Tentative flow chart of CMS Multi-Muon analysis

1 – DATASETS2 - RESOLUTIONS3 – FAKE RATES

4 – NUCLEAR INT MODEL5 – IP TEMPLATES MODEL

6 – SAMPLE COMPOSITION FITS7 – EXTENSION OF IP TO “SIGNAL REGION”

8 – SEARCH FOR ADDITIONAL MUONS9 – NEW PHYSICS MODELS

1 - DATASETS• DIMUON TRIGGERED DATA: “DIMUON”

– must try to avoid HLT enforcement of pixel-seeded tracks for muon candidates

– Reconstruct TIB/TID-seeded tracks in input to GM definition;

– Require last station to triggered muons– Apply Pt cut enforcement on muons– Apply || cut (ex. ||<2.4) on both legs– Apply quality cuts on event:

• Good run z<xx cm 2 < yy• ...

• SINGLE MUON DATA: “INCMU”– Reconstruct TIB/TID-seeded tracks– Reconstruct GM candidates similarly as above

• QCD JET TRIGGERED DATA (or Min Bias): “QCD”– Reconstruct TIB/TID-seeded tracks– Reconstruct GM candidates similarly as above

• MONTE CARLO SAMPLES:– QCD, with trigger simulation– heavy flavors, with DIMUON and INCMU trigger filters

TASKS:

1A) Understand how to reconstruct the data with special tracking, and verifythat V particles are found with large efficiency

1B) Decide “standard” muoncuts

1C) Get ready to produce sizable samples of MCaccording to our needs, byputting together cfg files andcards suitable to the task, andtrigger simulation

2 - RESOLUTIONS

• Search for J/psi and Y states in DIMUON and INCMU data

• Extract Pt resolution from scale fits (MuScleFit) of all resonances

• Extract IP resolution from sidebands-subtraction method on Y states

• Verify MC simulation

TASKS:

2A) Construct filter for resonances

2B) Construct macro whichextracts IP resolution andcompares to MC

2C) Scale fits to low-mass resonances

3 – FAKE PROBABILITIES

• Study two-prong hadronic decays in QCD data: K, p, KK, DK – Match legs to muon

candidates– Extract Pfake(), Pfake(K),

Pfake(p) as a function of track Pt and rapidity

– Check flatness of Pfake vs IP, Rdec

– Verify whether rates are consistent with QCD MC simulation

TASKS:

3A) prepare macros that extractfake rates from all resonances

3B) show that D can be found

3C) Put together tool to verify fake rates with Monte Carlo simulation

4 – NUCLEAR INT MODEL• Find 2-pronged vertices in QCD

data• Attach additional tracks with

simple chisquared method• Match multiplicity and Rdec

distributions with MC expectations – obtain scale factor

• Extract prediction for single-prong component from MC as ratio WRT reconstructed 2-prongs

• Determine hadronic composition of charged tracks from MC

• Can then extrapolate on DIMUON data using obseved 2-prongs there

TASKS:

4A) Put together tool to add tracksto 2-pronged vertices found by V0Producer

4B) Verify feasibility of method

4C) Verify uncertainties due to knowledge of hadron composition

5 – IP TEMPLATES MODEL

– b template:• search for DK signal close to muon in INCMU sample, extract

IP of muon from b with sidebands-subtraction method• Check with MC simulation• Can derive expected b fraction in DIMUON data by counting D

signal as a x-check– c template:

• Can try to search for DK signal opposite to muon in INCMU sample, deriving IP distribution of charm-enriched data; required b-component subtraction may make this difficult in practice

• Or can get from MC simulation • Other ideas needed

– Punch-through & DIF:• Get IP distributions of muons from application of P fake(,K,p) to

expected mixture of hadrons in QCD MC simulation; check result on QCD data; use same method on DIMUON data may obtain both shape AND normalization (within largish error) which can be useful in 2D fit to IP distributions

– Nuclear interactions component:• verify & (if needed) rescale amount of N.I./evt with different

multiplicities as estimated from MC, using vertices found in QCD data & MC

• Apply Pfake to N.I. tracks & extract IP distribution and expected normalization

– Prompt component:• Get from Y resonances

TASKS:

5A) Find D signal in B sim

5B) Understand how to extract c template

5C) Apply fake param to QCD simulation and verify thatIP distribution agrees

6 - SAMPLE COMPOSITION FITS

• Once all templates (with estimates for their normalization in case of PT and NI) are ready, one can do a 2-D fit to DIMUON data and extract the various components, in a controlled region: – IP<0.5cm– May want to require innermost pixel

layer has been hit by muon tracks– Can check results for b-fraction

using D signal– Should be able to verify fake and NI

component by relaxing constraints in global fit

TASKS:

6A) Put together fitter

6B) Develop filter for trackpairs not hitting inner pixels

7 - EXTRAPOLATION

• Once sample is understood (might require a lot of work!), can extrapolate results to larger IP region and/or no hit in innermost pixel layer– Verify shape and

normalization of events with large IP

– Can study quality of muons in this “signal region”

– Characterization of sample in terms of kinematics

TASKS:

7A) Understand how to best definesignal box

7B) Perform pseudoexperiment to verify sensitivity to unknown component

8 – SEARCH FOR ADDITIONAL MUONS

• Go back to low-IP sample and verify prediction for number of additional muons

• Predict number and IP distribution of additional muons in sample with large IP of triggering muons– For prompt muons, use rate of

additional muons in Y events– For b- and c- component, use real

muon estimate of MC and fake rate prediction applied to all tracks

– For PT and NI, use method already outlined above

TASKS:

8A) Determine sensitivity withpseudoexperiment

9 – NEW PHYSICS MODELS

• Generate MC sample modeling suitable new-physics hypothesis– Reconstruct and filter with

DIMUON trigger simulation and preselection cuts

– Verify sensitivity of signal boxes to NP model

– Verify sensitivity of counting method to NP model

TASKS:

9A) Generate sample

9B) Study how search strategycan be improved / tailored toconsidered new physics signal